Top DevOps Jobs in Dublin

Design, deploy, and optimize Azure-based database platforms (SQL, Cosmos DB, PostgreSQL, Redis). Implement backup/disaster recovery, performance tuning, IaC automation (Terraform/Bicep), CI/CD for database deployments, monitoring, security/compliance, and collaborate with development teams on data modeling and query optimization.

Design, implement, and optimize Azure-based database solutions (SQL, Cosmos DB, PostgreSQL, Redis). Ensure high availability, backup/recovery, performance tuning, IaC-driven deployments (Terraform/Bicep), CI/CD integration, monitoring, security/compliance, and cross-team collaboration with documentation and knowledge sharing.

Design, implement, and optimize Azure-based database solutions (SQL, Cosmos DB, PostgreSQL). Ensure performance, scalability, high availability, backup/recovery, security/compliance, automate deployments with IaC, monitor systems, troubleshoot issues, and collaborate with development teams on data modeling and query optimization.

Design, implement, optimize, and maintain Azure-based database solutions. Ensure high availability, performance tuning, backup/recovery and disaster recovery. Automate deployments via IaC, support schema and query optimization, monitor systems, enforce security/compliance, and share documentation and knowledge across teams.

Design, implement, optimize, and maintain Azure database solutions (SQL, Cosmos DB, PostgreSQL, Redis). Automate deployments with IaC, ensure backup/recovery and compliance, monitor performance, troubleshoot issues, and collaborate with development teams on data modeling and query optimization.

Design, implement, optimize, and maintain Azure-based database solutions. Automate deployments with IaC, ensure backup/recovery and compliance, monitor performance, troubleshoot issues, and collaborate with development teams for schema and query optimization.

Design, implement, optimize, and maintain Azure-based database solutions. Ensure high availability, backup/disaster recovery, security compliance, performance tuning, automation via IaC, monitoring, and collaborate with development teams on schema and query optimization.

Design, implement, and optimize Azure-based database solutions (SQL, Cosmos DB, PostgreSQL, Redis). Ensure performance, scalability, backup/recovery, high availability, security compliance. Automate deployments with IaC (Terraform/Bicep), support data modeling and query optimization, monitor systems, troubleshoot issues, document and share knowledge with teams.

Lead technology and cyber risk management for the bank's 2nd Line, advising on regulatory requirements (resiliency, outsourcing, privacy, AI, cloud), reviewing impacts and significant security events, applying data analytics to assess controls, and partnering with stakeholders to embed compliant, risk-mitigating practices.

Lead and develop globally distributed Data and AI teams to deliver production Data/AI solutions. Drive talent development, operational excellence, stakeholder alignment, and responsible AI practices while partnering with Product and Engineering to set priorities, roadmaps, and delivery metrics.

Lead technical pre-sales for enterprise ServiceNow solutions across a portfolio in Ireland. Engage C-suite, run demos, design solutions, respond to RFPs, support POCs, and collaborate with sales and professional services to drive deals and transitions.

Own and evolve Mastercard's AI-native data platform and applications: define roadmap, treat data as product with SLAs and governance, lead cross-functional teams, operationalize agentic AI and HITL workflows, ensure regulatory and security compliance, and translate regional customer needs into scalable data products.

Own and evolve an AI-native data platform and products: define roadmap and backlog, treat data as a product with SLAs and governance, transform structured/unstructured data into reusable schemas and datasets, lead cross-functional teams, operationalize agentic AI and HITL workflows, ensure compliance with security/privacy, translate regional needs into scalable models, analyze market trends, and drive product delivery within budget and timelines.

Lead product strategy and execution for Mastercard's AI-native data platform and products. Define roadmaps, data-as-product SLAs, governance, reusable data primitives and agentic AI/HITL workflows. Manage cross-functional teams, ensure compliance with security/privacy/regulatory requirements, translate regional needs, and deliver scalable data models, APIs, dashboards and datasets to meet business objectives.

As the Lead Program Security Engineer, you'll ensure security within Mastercard's Data and AI initiatives by implementing secure practices, architecture, and risk management across teams and products.

Own and evolve Mastercard's AI-native data platform and products: define roadmaps, treat data as a product with SLAs and governance, lead cross-functional teams, operationalize agentic AI and HITL workflows, ensure compliance with security/privacy/regulatory teams, and translate regional requirements into scalable data models and datasets.

Own and evolve Mastercard's Data & AI platform and products: define roadmaps, treat data as a product, lead cross-functional teams, ensure governance and compliance, operationalize agentic AI and HITL workflows, translate regional requirements, and deliver scalable, high-quality data products.

Own and evolve an AI-native data platform and applications: define roadmap and backlog, treat data as a product with SLAs and governance, lead cross-functional teams to build reusable data primitives, ontologies and datasets, operationalize agentic AI and HITL workflows, ensure compliance with security/privacy/regulatory requirements, and translate regional customer needs into scalable solutions.

Own and evolve an AI-native data platform and products: define roadmap, treat data as product with SLAs and governance, lead cross-functional teams to build reusable data primitives, ontologies, APIs and workflows, operationalize agentic AI/HITL processes, ensure compliance and stakeholder alignment, and drive product strategy and delivery.

Own and evolve an AI-native data platform and applications: define roadmap and backlog, treat data as product with SLAs and governance, convert Mastercard data into reusable data primitives and schemas, lead cross-functional teams, partner with security/compliance/privacy/legal, operationalize agentic AI and HITL workflows, and drive product strategy, delivery, and stakeholder communication.

Own and evolve an AI-native data platform and applications: define roadmap, treat data as product, establish SLAs and governance, lead cross-functional teams, operationalize agentic AI and HITL workflows, ensure compliance, and translate regional needs into scalable data products.

Lead product strategy and execution for Mastercard's Data & AI platform. Define roadmaps, data-as-product SLAs, ontologies, and reusable datasets. Drive cross-functional development, ensure compliance and security, operationalize agentic AI and HITL workflows, and align regional requirements to deliver scalable, user-centric data products.

Senior engineering leader responsible for leading and growing teams to deliver AI-first platforms and critical technical initiatives. Owns architecture, delivery practices, reliability (SLOs/SLIs), documentation standards, AI-augmented workflows, and cross-functional coordination. Represents engineering at executive level, drives talent strategy, succession planning, and organizational-scale technical direction to ensure high-quality, resilient, and efficient delivery.

Lead international commercial build for data, engineering and AI: own data foundation, shared engineering pool, solution architecture, AgentOps, AI evaluation, model routing and CIO platform integration to deliver production-grade, governed AI and data products.

Lead security partner for Data Commercialization and AI programs: advise on secure design, translate policies into actionable guidance, lead security reviews (threat models, code/design reviews), embed controls in SDLC, support vulnerability management, and drive security automation and standards across data and AI platforms.